11 research outputs found
Bio-AIMS collection of chemoinformatics web tools based on molecular graph information and artificial intelligence models
[Abstract] The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.Red Gallega de Investigación y Desarrollo de Medicamentos; R2014/025Instituto de Salud Carlos III; PI13/0028
Mature Andean forests as globally important carbon sinks and future carbon refuges
It is largely unknown how South America’s Andean forests affect the global carbon cycle, and thus regulate climate change. Here, we measure aboveground carbon dynamics over the past two decades in 119 monitoring plots spanning a range of >3000 m elevation across the subtropical and tropical Andes. Our results show that Andean forests act as strong sinks for aboveground carbon (0.67 ± 0.08 Mg C ha−1 y−1) and have a high potential to serve as future carbon refuges. Aboveground carbon dynamics of Andean forests are driven by abiotic and biotic factors, such as climate and size-dependent mortality of trees. The increasing aboveground carbon stocks offset the estimated C emissions due to deforestation between 2003 and 2014, resulting in a net total uptake of 0.027 Pg C y−1. Reducing deforestation will increase Andean aboveground carbon stocks, facilitate upward species migrations, and allow for recovery of biomass losses due to climate change.Fil: Duque, Alvaro. Universidad Nacional de Colombia; ColombiaFil: Peña, Miguel A.. Universidad Nacional de Colombia; ColombiaFil: Cuesta, Francisco. Universidad de Las Américas; EcuadorFil: González Caro, Sebastián. Universidad Nacional de Colombia; ColombiaFil: Kennedy, Peter. University of Minnesota; Estados UnidosFil: Phillips, Oliver L.. University of Leeds; Reino UnidoFil: Calderón Loor, Marco. Universidad de Las Américas; EcuadorFil: Blundo, Cecilia Mabel. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Carilla, Julieta. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Cayola, Leslie. Missouri Botanical Garden; Estados UnidosFil: Farfán Ríos, William. Washington University in St. Louis; Estados UnidosFil: Fuentes, Alfredo. Missouri Botanical Garden; Estados UnidosFil: Grau, Hector Ricardo. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Homeier, Jürgen. Universität Göttingen; AlemaniaFil: Loza-Rivera, María I.. Missouri Botanical Garden; Estados UnidosFil: Malhi, Yadvinder. University of Oxford; Reino UnidoFil: Malizia, Agustina. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Malizia, Lucio Ricardo. Universidad Nacional de Jujuy; ArgentinaFil: Martínez Villa, Johanna A.. Université du Québec a Montreal; CanadáFil: Myers, Jonathan A.. Washington University in St. Louis; Estados UnidosFil: Osinaga Acosta, Oriana. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Peralvo, Manuel. No especifíca;Fil: Pinto, Esteban. No especifíca;Fil: Saatchi, Sassan. Jet Propulsion Laboratory; Estados UnidosFil: Silman, Miles. Center For Energy, Environment And Sustainability; Estados UnidosFil: Tello, J. Sebastián. Missouri Botanical Garden; Estados UnidosFil: Terán Valdez, Andrea. No especifíca;Fil: Feeley, Kenneth J.. University of Miami; Estados Unido
Mature Andean forests as globally important carbon sinks and future carbon refuges
It is largely unknown how South America’s Andean forests affect the global carbon cycle, and thus regulate climate change. Here, we measure aboveground carbon dynamics over the past two decades in 119 monitoring plots spanning a range of >3000 m elevation across the subtropical and tropical Andes. Our results show that Andean forests act as strong sinks for aboveground carbon (0.67 ± 0.08 Mg C ha−1 y−1) and have a high potential to serve as future carbon refuges. Aboveground carbon dynamics of Andean forests are driven by abiotic and biotic factors, such as climate and size-dependent mortality of trees. The increasing aboveground carbon stocks offset the estimated C emissions due to deforestation between 2003 and 2014, resulting in a net total uptake of 0.027 Pg C y−1. Reducing deforestation will increase Andean aboveground carbon stocks, facilitate upward species migrations, and allow for recovery of biomass losses due to climate change.Fil: Duque, Alvaro. Universidad Nacional de Colombia; ColombiaFil: Peña, Miguel A.. Universidad Nacional de Colombia; ColombiaFil: Cuesta, Francisco. Universidad de Las Américas; EcuadorFil: González Caro, Sebastián. Universidad Nacional de Colombia; ColombiaFil: Kennedy, Peter. University of Minnesota; Estados UnidosFil: Phillips, Oliver L.. University of Leeds; Reino UnidoFil: Calderón Loor, Marco. Universidad de Las Américas; EcuadorFil: Blundo, Cecilia Mabel. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Carilla, Julieta. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Cayola, Leslie. Missouri Botanical Garden; Estados UnidosFil: Farfán Ríos, William. Washington University in St. Louis; Estados UnidosFil: Fuentes, Alfredo. Missouri Botanical Garden; Estados UnidosFil: Grau, Hector Ricardo. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Homeier, Jürgen. Universität Göttingen; AlemaniaFil: Loza-Rivera, María I.. Missouri Botanical Garden; Estados UnidosFil: Malhi, Yadvinder. University of Oxford; Reino UnidoFil: Malizia, Agustina. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Malizia, Lucio Ricardo. Universidad Nacional de Jujuy; ArgentinaFil: Martínez Villa, Johanna A.. Université du Québec a Montreal; CanadáFil: Myers, Jonathan A.. Washington University in St. Louis; Estados UnidosFil: Osinaga Acosta, Oriana. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Peralvo, Manuel. No especifíca;Fil: Pinto, Esteban. No especifíca;Fil: Saatchi, Sassan. Jet Propulsion Laboratory; Estados UnidosFil: Silman, Miles. Center For Energy, Environment And Sustainability; Estados UnidosFil: Tello, J. Sebastián. Missouri Botanical Garden; Estados UnidosFil: Terán Valdez, Andrea. No especifíca;Fil: Feeley, Kenneth J.. University of Miami; Estados Unido
Elevation and latitude drives structure and tree species composition in Andean forests: Results from a large-scale plot network
Our knowledge about the structure and function of Andean forests at regional scales remains limited. Current initiatives to study forests over continental or global scales still have important geographical gaps, particularly in regions such as the tropical and subtropical Andes. In this study, we assessed patterns of structure and tree species diversity along ~ 4000 km of latitude and ~ 4000 m of elevation range in Andean forests. We used the Andean Forest Network (Red de Bosques Andinos, https://redbosques.condesan.org/) database which, at present, includes 491 forest plots (totaling 156.3 ha, ranging from 0.01 to 6 ha) representing a total of 86,964 identified tree stems ≥ 10 cm diameter at breast height belonging to 2341 identified species, 584 genera and 133 botanical families. Tree stem density and basal area increases with elevation while species richness decreases. Stem density and species richness both decrease with latitude. Subtropical forests have distinct tree species composition compared to those in the tropical region. In addition, floristic similarity of subtropical plots is between 13 to 16% while similarity between tropical forest plots is between 3% to 9%. Overall, plots ~ 0.5-ha or larger may be preferred for describing patterns at regional scales in order to avoid plot size effects. We highlight the need to promote collaboration and capacity building among researchers in the Andean region (i.e., South-South cooperation) in order to generate and synthesize information at regional scale.Fil: Malizia, Agustina. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Blundo, Cecilia Mabel. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Carilla, Julieta. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Osinaga Acosta, Oriana. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Cuesta, Francisco. Universidad de Las Américas; Ecuador. Consorcio para el Desarrollo Sostenible de la Ecorregión Andina; EcuadorFil: Duque, Alvaro. Universidad Nacional de Colombia. Sede Medellín; ColombiaFil: Aguirre, Nikolay. Universidad Nacional de Loja. Centro de Investigaciones Tropicales del Ambiente y la Biodiversidad; EcuadorFil: Aguirre, Zhofre. Universidad Nacional de Loja. Centro de Investigaciones Tropicales del Ambiente y la Biodiversidad; EcuadorFil: Ataroff, Michele. Universidad de Los Andes; VenezuelaFil: Baez, Selene. Escuela Politécnica Nacional; EcuadorFil: Calderón Loor, Marco. Universidad de Las Américas; Ecuador. Deakin University; AustraliaFil: Cayola, Leslie. Herbario Nacional de Bolivia; Bolivia. Missouri Botanical Garden; Estados UnidosFil: Cayuela, Luis. Universidad Rey Juan Carlos; EspañaFil: Ceballos, Sergio Javier. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Cedillo, Hugo. Universidad de Cuenca; EcuadorFil: Farfán Ríos, William. Universidad Nacional de San Antonio Abad del Cusco. Herbario Vargas; PerúFil: Feeley, Kenneth J.. University of Miami; Estados UnidosFil: Fuentes, Alfredo Fernando. Herbario Nacional de Bolivia; Bolivia. Missouri Botanical Garden; Estados UnidosFil: Gámez Álvarez, Luis E.. Universidad de Los Andes; VenezuelaFil: Grau, Hector Ricardo. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Homeier, Juergen. Universität Göttingen; AlemaniaFil: Jadan, Oswaldo. Universidad de Cuenca; EcuadorFil: Llambi, Luis Daniel. Escuela Politécnica Nacional; EcuadorFil: Loza Rivera, María Isabel. University of Missouri; Estados Unidos. Herbario Nacional de Bolivia; Bolivia. Missouri Botanical Garden; Estados UnidosFil: Macía, Manuel J.. Universidad Autónoma de Madrid; EspañaFil: Malhi, Yadvinder. University of Oxford; Reino UnidoFil: Malizia, Lucio Ricardo. Universidad Nacional de Jujuy. Facultad de Ciencias Agrarias; ArgentinaFil: Peralvo, Manuel. Consorcio para el Desarrollo Sostenible de la Ecorregión Andina; EcuadorFil: Pinto, Esteban. Consorcio para el Desarrollo Sostenible de la Ecorregión Andina; EcuadorFil: Tello, Sebastián. Missouri Botanical Garden; Estados UnidosFil: Silman, Miles. Center for Energy, Environment and Sustainability; Estados UnidosFil: Young, Kenneth R.. University of Texas at Austin; Estados Unido
EU-OPENSCREEN. Working in partnership in Chemical Biology and early Drug Discovery across Europe
EU-OPENSCREEN es un consorcio de infraestructura de investigación europea que asiste a todas las etapas de un proyecto de desarrollo de herramientas químicas, trabajo con una base de datos de acceso abierto y una colección común y única. Tiene más de 20 instalaciones químicas que proporcionan a los investigadores el acceso a tecnologías de vanguardia para desarrollar sus propias herramientas. Su objetivo es apoya la competitividad científica y económica global de Europa.N
Analysis of the scientific competency questions followed by the IMI OpenPHACTS consortium for the development of the semantic web-based molecular information system OPS
Molecular information systems play an important role in modern data-driven drug discovery. They do not only support decision making but also enable new discoveries via association and inference. Herein we outline the scientific requirements followed by the IMI Open PHACTS consortium for the design of the OPS information system built on the integration of compound-target-pathway-disease/phenotype data. Typical scientific competency questions provided by the consortium members will be analyzed based on the underlying data concepts and data associations needed to answer the questions. Publicly available data sources will be listed and the need and potential of semantic web-based technology will be presented
Scientific competency questions as the basis for semantically enriched open pharmacological space development
Molecular information systems play an important part in modern data-driven drug discovery. They do not only support decision making but also enable new discoveries via association and inference. In this review, we outline the scientific requirements identified by the Innovative Medicines Initiative (IMI) Open PHACTS consortium for the design of an open pharmacological space (OPS) information system. The focus of this work is the integration of compound-target-pathway-disease/phenotype data for public and industrial drug discovery research. Typical scientific competency questions provided by the consortium members will be analyzed based on the underlying data concepts and associations needed to answer the questions. Publicly available data sources used to target these questions as well as the need for and potential of semantic web-based technology will be presented.The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no. [115191], resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and inkind contribution of EFPIA companies
Scientific competency questions as the basis for semantically enriched open pharmacological space development
Molecular information systems play an important part in modern data-driven drug discovery. They do not only support decision making but also enable new discoveries via association and inference. In this review, we outline the scientific requirements identified by the Innovative Medicines Initiative (IMI) Open PHACTS consortium for the design of an open pharmacological space (OPS) information system. The focus of this work is the integration of compound-target-pathway-disease/phenotype data for public and industrial drug discovery research. Typical scientific competency questions provided by the consortium members will be analyzed based on the underlying data concepts and associations needed to answer the questions. Publicly available data sources used to target these questions as well as the need for and potential of semantic web-based technology will be presented.The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no. [115191], resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and inkind contribution of EFPIA companies